An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester

<table class="fixed-width table-group" id="tab13"><tr><td><table class="table"><colgroup><col style="width:9.09em"/><col style="width:5.48em"/><col style="width:6.01em"/><col style="width:5.14em"/></colgroup><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr class="thead"><td class="align_left">Characteristics</td><td class="align_center">Prediction</td><td class="align_center">Experiment</td><td class="align_center">Error (%)</td></tr><tr><td class="thead-hr" colspan="4"><hr/></td></tr><tr><td class="align_left">Displacement (<i>μ</i>m)</td><td class="align_center">330.68</td><td class="align_center">326.0174</td><td class="align_center">1.43</td></tr><tr><td class="align_left">Stress (MPa)</td><td class="align_center">140.6496</td><td class="align_center">139.4822</td><td class="align_center">0.83</td></tr><tr><td class="align_left">Safety factor</td><td class="align_center">3.5952</td><td class="align_center">3.5872</td><td class="align_center">0.22</td></tr><tr class="table-tr"><td colspan="4"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

<div>Competition predicted and experimental results.</div>

Mathematical Problems in Engineering

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Table 13

Table 13: An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester 

Table 13 | An Efficient Hybrid Approach of Finite Element Method, Artificial Neural Network-Based Multiobjective Genetic Algorithm for Computational Optimization of a Linear Compliant Mechanism of Nanoindentation Tester 